Fluorescence microscopy has allowed studying dynamical biological processes in vivo with an ever increasing accuracy. Nonetheless, the physically inherent resolution limits impede the study of very dynamical intracellular processes such as microtubule dynamics. One way to overcome this limited resolution is to reconstruct the underlying object dynamics from the image data by using Bayesian statistics. This framework allows combining statistical models about the image formation process and the dynamical process driving the biological function under scrutiny. In this work we show that the accuracy and robustness of tracking microtubule dynamics can be improved by imposing a weak dynamical prior about the hidden geometry of the microtubule and by accounting for the overall photobleaching.
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